Dr. Imran Afgan
Dr. imran afgan Associate Professor Mechanical & Nuclear Engineering

Contact Information
imran.afgan@ku.ac.ae +971 2 312 4258

Biography

Dr. Imran Afgan is a specialist in massively parallel computing and has a special interest in high fidelity simulations (Large Eddy Simulations & Direct Numerical Simulations). After graduating in Mechanical engineering from GIK Institute of Engineering Sciences and Technology Pakistan in 1999, he began his career as a research engineer in Shanghai Nuclear Engineering Research and Design Institute China. After successful completion of his PhD in Mechanical Engineering from The University of Manchester in 2007, he joined the Université Pierre et Marie Curie and Électricité de France (edf) as a research scientist. In 2011 he moved back to The University of Manchester in an academic role where he served as a senior lecturer/associate professor before moving to Khalifa university in 2019. 

His active areas of research include, Turbulence Modelling, conjugate heat transfer, Uncertainty Quantification, Machine Learning, Fluid Structure Interaction, Aeroacoustics, hybrid dual mesh methods and Wall functions development. His applied research in the areas of Nuclear thermal Hydraulics, Renewable Energy (wind/tidal, solar thermal) and energy storage has led to a number of successful grants with a total funding income of over USD 6 million. He has been the lead researcher in Performance Assessment of Wave and Tidal Array System (PerAWAT) funded by DNV-GL, Reliable Data Acquisition Platform for Tidal (ReDAPT) funded and commissioned by Energy Technology Institute (ETI) and Computations for Advanced Reactor Engineering (CARE) funded by EPSRC (2011-2012). He was the CoI in Extreme Loading of Marine Energy Devices due to Waves, Current, Flotsam and Mammal Impact (X-Med) funded by EPSRC (2012-2015) and Hybrid RANS/LES developments funded by Siemens (2016-2018) and PI in Nuclear Energy and Trainings (NEaT) (2018-2019) funded by the UK Department for Business, Energy and Industrial Strategy (BEIS). He was also the PI of Engineering Sustainable Solar Energy and Thermocline Alternatives (ESSEnTiAl) (2018-2020) funded by BEIS and a CoI in ORE EPSRC Supergen Offshore Renewable Energy Hub (2018-2022) and A New Technology Innovation for Foreign Object Debris removal (ANTIFOD)-Horizon 2020 (2018-2022). Currently he is the PI/Co.I on multiple grants from the Ministry of Education UAE, Khalifa University and ASPIRE/ADEK UAE on FSI of thermal hydraulics, Accident Tolerant fuels for APR 1400, Molten Corium Concrete Interaction (MCCI) and Ship Wake Aerodynamics.


Education
  • PhD Mechanical Engineering, University of Manchester, United Kingdom
  • BS Mechanical Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences & Technology, Topi, Pakistan

Teaching
  • Advanced Fluid Mechanics (MEEN 604)
  • Advanced Viscous Flow Analysis (MEEN 612 )
  • Computation Fluid Mechanics (MEEN 721 )
  • Fluid Mechanics (MEEN 335 )
  • Heat Transfer (MEEN 343)
  • Special Topics in Mechanical Engineering (MEEN 495)

Affiliated Centers, Groups & Labs

Research
Research Interests
  • Nuclear thermal Hydraulics
  • Renewable Energy (wind/tidal, solar thermal)
  • Advanced methods in CFD for multiphysics applications

Research Projects

Enhancing modelling and simulation tools using uncertainty quantification and machine learning for multi-physics problems.

Nuclear and hydro power generation techniques have an important role to play in UAE’s 2030 energy vision of low carbon sources to meet future energy demand. UAE is currently investing in installation of a number of conventional hydro power plants and its first nuclear power plant, Barakah. For these plants to operate at high efficiencies and to satisfy stringent safety requirements a step-change is consequently needed in modelling and simulation capabilities; to accurately describe the multi-physics (coupled thermal hydraulics and solid mechanics) processes. This research not only targets the wider thermal-hydraulics modelling/design planned activities of UAE’s 2030 energy vision but also directly supports the “UAE Strategy for Artificial Intelligence (AI)” which emphasis strongly on the automation of renewable energy and space sectors. The main objectives of this research are to 1) enhance the modelling and simulation tools for Fluid Structure Interactions (FSI) and Conjugate-Heat-Transfer (CHT), which govern plant steady and transient operations. 2) develop reliable and versatile physical models for modelling and simulation algorithms.

Thermal analysis of baffle jetting in fuel rod assembly

For nuclear power plants, flow-induced vibrations may occur within the reactor core, heat exchangers, and steam generators. For pressurized-water nuclear reactors (PWR), cold water flows within the reactor core to extract heat generated by the fuel rods. The flow is mainly upward axial and parallel to the fuel rods and may cause rod vibrations. However, a part of the flow passes horizontally through the gaps between the baffle plates surrounding the core, this leads to a transverse turbulent jet impinging the rods. This particular non-uniform cross-flow, known as baffle jetting, induces rod vibrations and is the cause of many grid-to-rod fretting problems.

Engineering Sustainable Solar Energy and Thermocline Alternatives 

Parabolic trough CSP works on the principle of harnessing solar thermal energy which is used to heat up a working fluid thereby generating electricity via steam; excess heat can also be stored in thermal storage tanks, thus leading to an uninterrupted power in contrast to other RE resources. The two main goals of this research are: 1) Enhancement of energy production from CSP via use of Nano-Particles (nanoparticles) and induced swirl using experiments and simulations. 2) Improvement of efficiency and design of thermocline energy storage systems.


Research Staff and Graduate Students:

Staff
Shahid Rabbani Dr.
Mohamed Ali Dr.
Ilyas Khurshid Dr.
Students
Mariam Nagi Amer Ms.
Ahmed Salih Abuelyamen Mr.
Kamran Mukhtar Ahmed Mahboob Mr.
Tauha Irfan Khan Mr.
Saleh Mohamed Husain Mohamed Mr.
Kaleemullah Mohammed Mr.
Khaled Yaqoob Yousef Mohamed Alhammadi Mr.
Samah Ahmed Albdour Ms.
Sameer Mohammad Osman Mr.
Neelam Jehan Abduk Majeed Ms.
Surya Pralash Gajagouni Mr.
Muhammad Muhammad Ishrat Faizan Mr.